CN106605158B - It is simulated using the Sediment transport for cuing open the parameterized template drawn for depth - Google Patents
It is simulated using the Sediment transport for cuing open the parameterized template drawn for depth Download PDFInfo
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Abstract
For at least one step-length in simulation, depth-averaged flow analogue system provided in this article and method are cutd open for dynamic depth using parameterized template and are drawn.In an illustrative computer based embodiment, analogy method includes, for each point map at a given time step: depth-averaged deposit concentration and depth-averaged flow velocity based on the different grain size grade of the point map determine flowing template and deposit concentration template；The vertical distribution deposit concentration section and vertical distribution fluid velocity profile of the associated grain size category of the point map are constructed using template, to obtain 3D flow velocity and 3D deposit concentration field；Use 3D field computation fluid and sediment flux；Divergence based on the flux updates flow velocity and deposit concentration section；It is quadratured to section to calculate the depth-averaged flow velocity of update and deposit concentration and center of gravity；And depth-averaged flow equation is solved for future time step-length.
Description
Background technique
Current many oil-gas reservoirs are formed and the fluid in fossil basin flows sedimentary deposit.Fluid flowing migration is heavy
Product object sorts and is optionally deposited different size of particle, to form the deposition with predictable geometry and property
Body.If process can be simulated conscientiously in this way with enough precision, subsurface reservoir is actually modeled as possibility.Petroleum and
The input that gas industry expectation geological model is simulated as reservoir Dynamic, this is used to select the position of new well, estimation oil gas storage
Amount and plan reservoir exploitation strategy.Geological model is specified for characterizing reservoir Dynamic and determining that the crucial of productibility of reservoir is joined
Number (spatial distributions of such as fluid properties and permeability).(for sandstone reservoir, the spatial distribution of permeability is to form the reservoir
Sand size distribution, by plasma to the mineralogy of the division of those sand and the reservoir and the function of burial history.) more
Actual model enables industry to work out more optimized production strategy
Many different types of measurement data can be used in Geologic modeling process, including but not limited to from rock core, well logging day
The rock property data that will, seismic data, well testing and creation data obtain, and limit the structure of the not same district in the model space
And stratal surface.Under normal conditions, the resolution ratio of available measurement data or space covering are not enough to uniquely determine geological model
The rock property at each point in space.Therefore, if the sector has formulated drying method to fill the data of loss, including it is right
The simulation of Sediment transport and deposition process.
Such process simulation is attempted in various ways, comprising: solves full 3D liquid flow equation；Use object
One group of simpler phenomenological equation of reason reduction strategy and solution, and solve one group of 2D depth-averaged flow equation.When to entire
When the useful room and time resolution ratio of reservoir and/or basin scale is attempted, full 3D fluid-flow analogy computationally takes
With excessively high.Physics reduction strategy simulates Sediment transport using heuristic rule or random walk process, but is limited
The artifact and numerical value noise level of the practicality processed.Existing depth-averaged flow simulating can be using classical St.Venant shallow water
Equation (St.Venant shallow water equations) or the three or four equation turbidity current models of Parker come obtain relative to
The significant calculating advantage of full 3D fluid-flow analogy.
Therefore, many engineer applications are widely used in using the simulation of 2D depth-averaged flow equation.However, reservoir and/
Or in the case that basin models, many natural flowings are highl stratifications, and degeee of stratification is over time and space dynamically
Ground variation.Moreover, this layering is to the final geometry of deposited material and the crucial effect of property.For example, it is muddy to suspend
The feature of layering of the substance in flowing and dykes and dams argillaceous sediment is closely related.Depth in existing reservoir and/or basin
In average flow simulating, the loss of flowing and deposit concentration changeability in vertical direction and its in time and space
On corresponding variation estimated lead to significant error.
Summary of the invention
Therefore, disclosed herein is cut open the dynamic depth for drawing (profiling) for depth using dynamic parameter template to put down
Equal flow analogue system and method.This dynamic based on template, which is cutd open to draw, makes it possible to keep depth-averaged flow simulating method
Calculating advantage, especially in terms of their calculating speed, while the enough representativenesses for providing flow velocity and deposit concentration are hung down
Straight variation and its variation over time and space.
In an illustrative computer based embodiment, which includes that a given time is walked
Each point map of strong point: depth-averaged flow velocity and depth-averaged deposit concentration based on the point map determine flowing template
With at least one deposit concentration template；The vertical distribution flow velocity of the point map is constructed by using template using the template
Section and vertical distribution deposit concentration section flow and 3D deposit concentration field to rebuild 3D；Weight is used at each point map
The 3D field of flow built calculate each different grain size grade sediment flux and flowing flux；By calculating at each point map
The divergence of deposition flux update deposit concentration section；It quadratures to update depth-averaged deposit concentration and center of gravity；With
And field of flow and future time step-length solution depth-averaged flow equation are directed to using the value that these dynamics update.Deposit is dense
Degree section update operation may consider fluid velocity profile, bed surface shear stress, erosion, deposits, clear water carry secretly/roll out and
DIFFUSION IN TURBULENCE.At each point in a model, can each time step determine net deposits and recorded for
With post analysis.
In another embodiment, the computer based method for simulating the evolution of sedimentary basin includes: eachly
Figure point at, based on depth-averaged flow velocity and for associated grain size category one or more depth-averaged deposit concentrations come
Determine flowing template and at least one deposit concentration template, the depth-averaged flow velocity and one or more of depth-averageds
Each of deposit concentration is for the point map at given time step-length.This method further include: at each point map,
The flowing template is applied to the depth-averaged flow velocity and is applied at least one described deposit concentration template described
One or more depth-averaged deposit concentrations with obtain be directed to the point map vertical distribution fluid velocity profile and one or more
A vertical distribution deposit concentration section, to rebuild one for being directed to associated grain size category at the given time step
Or multiple 3D deposit concentrations field and 3D velocity field.This method further include: at each point map, using the 3D velocity field and
One or more of 3D deposit concentrations field calculates one or more sediment fluxes for associated grain size category
And fluid flux.In addition, this method comprises: at each point map, at the point map at given time step-length
The divergence of the fluid flux and one or more divergences of one or more of sediment fluxes update the fluid velocity profile
With one or more of deposit concentration sections.This method further include: at each point map, by given time step-length
The fluid velocity profile and one or more of deposit concentration sections of the point map at place are quadratured to calculate the depth
Mean flow rate and one or more of depth-averaged deposit concentrations are spent, thus obtain the 2D velocity field of update and update one
A or multiple 2D deposit concentration fields.In addition, this method comprises: each from the export of one or more of deposit concentration sections
The center of gravity of point map；And one or more 2D deposit concentrations field, center of gravity and the flowing of the 2D velocity field, update based on update
Height is come to one group of two-dimensional flow equation solution, to calculate the depth-averaged stream at future time step-length at each point map
Speed.
In another embodiment, a kind of Sedimentary Basin Evolution simulation system includes: the memory with simulator software；
It is coupled to the memory to execute the one or more processors of the simulator software, the software makes one or more
A processor performs the following operations in each of multiple time steps, comprising: at each point map, based on for correlation
The one or more depth-averaged deposit concentrations and depth-averaged flow velocity of the grain size category of connection determine flowing template and at least one
A deposit concentration template, each needle in the depth-averaged flow velocity and one or more of depth-averaged deposit concentrations
To the point map at given time step-length.The operation further includes at each point map, by the flowing template application
One or more of depth-averageds are applied to the depth-averaged flow velocity and by least one described deposit concentration template
Deposit concentration is dense for the vertical distribution fluid velocity profile of the point map and one or more vertical distribution deposits to obtain
Section is spent, to rebuild the one or more 3D deposit concentrations for being directed to associated grain size category at the given time step
Field and 3D velocity field.The operation further include: at each point map, use the 3D velocity field and one or more of 3D
Deposit concentration field calculates one or more sediment fluxes and fluid flux for associated grain size category.The behaviour
Work includes: to be at least partially based on the fluid velocity profile at the point map at given time step-length and one or more of
Deposit concentration section sinks at each point map as the net of the function of depth to record in non-transitory information storage medium
Product object deposition.In addition, the operation includes: at each point map, at the point map at given time step-length
The divergence of the fluid flux and one or more divergences of one or more of sediment fluxes update the fluid velocity profile
With one or more of deposit concentration sections.The operation further include: at each point map, by being walked to given time
The fluid velocity profile of the point map of strong point and one or more of deposit concentration sections are quadratured described to calculate
Depth-averaged flow velocity and one or more of depth-averaged deposit concentrations, to obtain 2D velocity field and the update of update
One or more 2D deposit concentrations field.The operation further include: every from the export of one or more of deposit concentration sections
The center of gravity of a point map.The operation further include: one or more 2D deposit concentrations of 2D velocity field, update based on update
Field, center of gravity and flowing height are come to one group of two-dimensional flow equation solution, to calculate at future time step-length at each point map
Depth-averaged flow velocity, future time step-length as the given time step-length and is repeated into the determination, application, use, note
Record updates, calculates, exports and solves operation.
Detailed description of the invention
In the accompanying drawings:
Fig. 1 and 2 is the map view and front view of a part of reservoir basin model.
Fig. 3 is the update front view of reservoir basin model.
Fig. 4 is the perspective view of reservoir basin model.
Fig. 5 is the map view of a solution of depth-averaged flow equation.
Fig. 6 A shows the illustrative flowing and concentration template of the embodiment from disclosed method, near bottom
With the speed close to zero and the top in flowing has the speed gradually increased；
Fig. 6 B show the embodiment from disclosed method it is another it is illustrative flowing and concentration template, have from
Zero starts and gradually increases with depth, but there are the deposit concentrations of small decline in bottom；
Fig. 6 C shows another illustrative flowing for specified particle size grade of the embodiment from disclosed method
With concentration template；
Fig. 7 is with via the illustrative depth-averaged for cuing open the Sediment transport that the parameterized template drawn determines for depth
The flow chart of flow simulating method.
Fig. 8 is illustrative depth-averaged flow analogue system.
Fig. 9 is illustrative software flow pattern.
It will be appreciated, however, that the specific embodiment provided in following the drawings and specific embodiments does not limit this public affairs
Open content.On the contrary, they for those of ordinary skill provide distinguish the alternative form included in the range of appended claims,
The basis of equivalent and other modifications.
Specific embodiment
It characterizes various sizes of in the complicated structure and sedimentary system of the lithosomic body of the crucial heterogeneity in oil-gas reservoir
The migration of sedimentary particle, erosion, deposition and assorting room are directly related.For example, forming the clast of delta or basin floor fan
The deposition of lithosomic body usually all flows into open area (such as from restricted channel (such as river mouth or submarine canyon mouth) with arsenicbearing gold ores
The pelagic zone of shallow river system or abyssal plain or Deep Water Basins in subsea environment) start.Wherein silt carrying flow enters
The point for depositing the open area occurred is commonly known as riverbed or valley mouthful, or is simply referred as the entrance of corresponding deposition basin.
Initially, this flowing spread and with flowing slow down deposition deposit.Hereafter, as the sediment of deposition grows tall, deposition
Sediment starts to hinder field of flow.Finally, deposition becomes sufficiently large, so that flowing is changed its course around deposition.This causes field of flow to arrive
Other than the past deposition or new path and entrance of the neighbouring open area of deposition in the past.Then deposition process repeats, and creates
The second main body in system.With additional main body is created, they may be overlapped and be stacked on main body previous.It is multiple
Main body can also create simultaneously with system.The stacking of obtained lithosomic body can indicate the structure of oil-gas reservoir.
According to the dynamic depth mean flow dynamic model proposed adoption of the disclosure to three-dimensional sedimentary deposit, their structure and rock
The numerical simulation based on physics of formation and the evolution of matter.By by obtained stratigraphic model, lithosomic body geometry and rock
Stone property is linked with associated deposition process and the control of corresponding geology, and this simulation can reduce RESERVOIR INTERPRETATION and characterization
In uncertainty.Their model fluids and Sediment transport Physics Work associated with sedimentary system extensive and
Running during long-term evolution, to successfully reproduce deposition structure and rock property in three-dimensional with high spatial resolution.
Seismic image based on subsurface volume, disclosed method, which makes it possible to construct, to be described in detail through subsurface volume
The geological model of size distribution.In at least some embodiments, this method is related to (1) using given primary condition and perimeter strip
Part comes using the flowing of numerical simulation calculation fluid and Sediment transport based on physics；(2) by fluid flowing and Sediment transport
It is corroded and sedimentation model couples invading with the sizes in each place in simulation system and the deposit of property with suitable
Erosion and deposition；(3) come the erosion and deposition of the deposit in each place in record system using three-dimensional grid scheme appropriate,
And the landform or the depth of water of the variation of the system；(4) the external control to system is safeguarded by dynamically changing boundary condition.
Fig. 1-4 depicts the various aspects of the model by disclosed method simulation.Fig. 1, which is depicted, to be had initial or develops
The map view of the fluid flowing 10 of flow boundary 12 and 14.Fluid flowing 10 via entrance 15 enter model area, it is described enter
Mouth 15 is centered in the origin of X and Y-axis for convenience.It is moved since the flowing that entrance issues is in positive x direction.In entrance 15
Place, flowing have original width 17 and half-breadth 8, and front end extends in positive x direction.It further depicts by flowing the deposition 16 formed
Profile.
Fig. 2 depicts the front view of the x-axis interception along Fig. 1, shows fluid flowing 10 and is layered as two layers.Fig. 2 will
Two layers of fluid is shown as clean layer 20 containing on sand bed 28, and wherein the upper bound is provided by sea level 21, and lower limit is by seabed 22
It provides.Muddy model is also referred herein as containing sand bed 28.Bottom height above sea level before deposition process occurs is 24.Containing at entrance 15
The height of husky water layer is 26.The height of arsenicbearing gold ores layer 28 is potentially based on position and changes, and is such as located at the x-axis further along Fig. 2
Difference height 27 shown in.
Fig. 3 depicts the front view intercepted after deposition has occurred and that along the x-axis of Fig. 1.As shown in Fig. 2, in Fig. 3
Fluid flowing is described as including containing the clean layer 20 on sand bed 28.Original bottom 24 is together with newly deposited sedimentary 36
Seabed height above sea level is changed into 30 by thickness.
As shown in figure 4, simulation operates threedimensional model space 111 how to form deposited material in bottom surface 117
Upper accumulation or the in other ways portrayal of the landform of influence bottom surface 117.When simulating completion, the model space will be comprising describing tool
There are sedimentation body 113 and the face boundary 115 in region of different nature.The model space may be used as the three-dimensional of model block (unit)
Array, each geology with distribution and/or Geophysical Properties, such as lithology, porosity, acoustic impedance, permeability, water saturation
It spends (such property will be collectively referred to as " rock property ").The target of Geologic modeling process is that rock property is distributed to Geological Model
Each model block in type space.Each unit in the model space even can be heavy with the detailed description of the function as the time
The history of product species type, volume and deposition rate is associated.The detailed model of obtained reservoir interval should suitable for estimation
The property of the rock property and industry characteristics and ambient substance of interval and overall basin.
Simulation process includes the operation in full three-dimensional domain and two-dimentional (depth-averaged) domain, and using parameterized template from one
It is converted to another.In three dimensions, allow the x-axis representation in components of flow velocity of the point (x, y, z) at time t for u (x, y, z, t).It allows
Other horizontal components (along y-axis) are expressed as v (x, y, z, t).Vertical (z-axis) component of flow velocity can be represented as w (x, y, z,
T), the considerations of but in order to support then in the form of entrainment and DIFFUSION IN TURBULENCE, it is considered inappreciable, and is hereafter ignored
(that is, being set as zero).Deposit concentration is distributed into frequency range (bin) (with D by partial sizeiThe representativeness for representing i-th of frequency range is straight
Diameter) and it is expressed as ci(x, y, z, t).This frequency allocation concentration can be referred to as " the deposition of given grain size category herein
Object concentration ".
In two dimension, the x-axis representation in components of depth-averaged flow velocity of the point (x, y) at time t is allowed to be U (x, y, t).Allow depth
The y-axis representation in components of degree mean flow rate is V (x, y, t) and the depth-averaged deposit concentration of frequency range i is expressed as Ci(x, y,
t).In addition, the depth of flow is allowed to be expressed as h (x, y, t).It conversion between two and three dimensions and then can be implemented as follows:
In equation (1)-(2), template f is floweduv() is used to each given time t with z-axis dependence
With depth-averaged velocity component U, V at point map (x, y).That is, flowing template is applied to depth-averaged velocity component, with true
Vertical distribution fluid velocity profile at fixed each time and point map.Equally, equation (3) is by concentration template fc() is applied to each
The depth-averaged deposit concentration of grain size category is with the vertical distribution deposit concentration section of the determining grain size category.(some
In embodiment, identical deposit concentration template is used for each grain size category, and other embodiments are dense using different deposits
It spends template and is used for each grain size category.)
Flowing and deposit concentration template are parameterized, that is, they are the depth of depth-averaged flow velocity (U, V), grain size category i
Spend average deposition object concentration CiSet function and optionally the flowing height h of fluid column and/or the function of center of gravity.(
In above-mentioned equation, h is only z-axis scale factor, and is not parameter).In addition, as deposit concentration substitution,
Template can be the function of the total sediment quality of depth-averaged at the time or point map, volume or deposit concentration.
Each template is uniformed, so that it is one along x-axis integral.Therefore, such as by above formula (4)-(6)
There is provided, depth-averaged flowing and depth-averaged deposit concentration can be quadratured by the x-axis of vertical distribution section come
It obtains.
The exact shape of template can be obtained from targeted experiment.Document shows, it is contemplated that such template tool
There is the character shape that can easily parameterize to reflect their use environment.For example, it is contemplated that uniform fluid flowing
With the vertical distribution fluid velocity profile for following power law, wherein index is changed based on speed to explain under higher shear stress
The generation of non-linear viscosity and turbulent flow.As another example, it is contemplated that the vertical distribution deposit concentration section (and because
The uniformity of this fluid flowing) rough tiered form is followed, there is speed to rely on transition acutance, be reflected in higher speed
Under mixing and turbulent flow based on shearing increasingly increased importance.Vertical distribution is pre- to the dependence of deposit concentration and flow velocity
Phase is interacted in a manner of it can be analyzed ground and/or analyze via laboratory experiment with determination shape of template appropriate and foot
Enough accurate parametrizations, with explain flow velocity and deposit concentration to it is each other people vertical distribution section shape influence.
In view of being previously used for the equation converted between two and three dimensions, simulation can be flowed using for fluid
The equation of modeling converts it into three-dimensional flow field using parameterized template to generate two-dimensional flow speed field.In one embodiment
In, by by u (x, y, z, t), v (x, y, z, t) and ciThe parametrization of (x, y, z, t) indicates to substitute into three-dimensional Navier-Stokes
Equation, and z-axis integral is executed on depth of flow h to obtain and can be solved with the differentiation in flow field determining by time step
Obtained depth-averaged flow equation is obtained by simulating equation used.
Although the vertical distribution that parameterized template is used for flow velocity and deposit concentration may be in equation and analog result
Middle generation different, but simulate still using the detailed rules for the implementation using depth-averaged flow equation proposed in document.It is special
It is not that depth-averaged flow method is based on following work: Parker G., Fukushima, Y. and Pantin, H.M., " Self-
accelerating turbidity currents",J.Fluid Mech.171,145-181,1986；Bradford,S.F.,
“Numerical modeling of turbidity current hydrodynamics and sedimentation”,PhD
Paper, U.Michigan, Ann Arbor, 1996；Bradford, S.F., Katopodes, N.D., and Parker, G.,
“Characteristic analysis of turbid underflows”,J.Hydraulic Eng.123,420-431,
1997；Imran, J., Parker, G., and Katopodes, N.D., " A numerical model of channel
inception on submarine fans",J.Geophys.Res.103(C1),1219-1238,1998；Bradford,
S.F.,Katopodes N.D.,“Hydrodynamics of Turbid Underflows I&II”,J.Hydraulic
Eng.125(10),1006-1028,1999；And Sun, T. etc., " Method for evaluating sedimentary
basin properties by numerical modeling of sedimentation processes”,US Pat.8,
117,019B2,2012。
As shown in above-mentioned work, depth-averaged flow equation executes certain conservation principle, i.e. the flowing of conservation is dynamic
Amount, troubling layer volume, sedimentary particle quality and (optional) include the energy of Turbulent Kinetic, to determine in each point map
The depth-averaged deposit concentration of each grain size category and the time-derivative of depth-averaged flow velocity.In embodiment, there are one group
Two-dimensional flow equation.Then time-derivative is combined with depth-averaged flow velocity and deposit concentration from previous step-length, with true
It is determined in the value of future time step-length.As explained further below, value can be carried out additionally in each time step
Adjustment is simulated and then is repeated to explain other phenomenons, iteratively determines the value for each time step being modeled.
Foregoing work uses can also the numerical simulation technology used by simulation system disclosed herein and method.
For example, can be using substitution gridding strategy, such as in entitled " Method for geological modeling
The International Patent Publication WO 2006/ of through hydrodynamics-based gridding (Hydro-Grids) "
Water conservancy grid (Hydro-Grid) method described in 007466.For solving the set of flow equation or the partial differential equation of group
(PDE) numerical stability that solver can at least be shown based on it is selected.In particular, Harten, Lax, van
Leer (" HLL ") solver may be preferred.Each arbitrary boundary conditions may be implemented in the model space, comprising: dry node, boundary wall
With standard open boundary condition, and the evolution on the new boundary including emerging dry node can be explained further.Generally directed to essence
Degree weighs analog rate to select the quantity of granularity frequency range, and the interpolation or dynamic of the granularity indicated by each frequency range adjust
Mitigate the loss of precision.
Fig. 5, which is shown, to use ash by the example of the simulator depth-averaged velocity field that step-length generates at any time
Degree is to indicate the overall flow rate in each unit.In the unit (for example, unit 71) far from basin entrance, speed ratio is attached in entrance
Close unit (for example, unit 73) is much lower.In order to convert the flowing with vertical change for two-dimensional depth mean flow rate field
, simulation application template.Fig. 6 A shows illustrative flowing template 602, in point map (for example, unit 71) vacation to give
If U, V, CiAt h value, there is the speed close to zero and the near top in flowing to have near bottom and gradually increase
Speed.
Similarly, Fig. 6 B shows illustrative deposit concentration template 604, at the parameter value of given point map, tool
Have and start from scratch and gradually increased with depth, but there are the deposit concentrations of small decline in bottom.As previously mentioned, some implementations
One deposit concentration template 604 is applied to all grain size categories by example, and other embodiments are by each deposit concentration mould
Plate is applied to different grain size categories.Fig. 6 C shows the deposit concentration template f of specified particle size gradeCi() 606, when with
When template 604 compares, increases faster with depth and remain broadly stable to the lower half of flowing.All other parameter phase
Deng template 606 may be than template 604 more suitable for small granularity, and template 604 can better adapt to big or middle granularity.Template
Region 612,614,616 is respectively equal to one.
Fig. 7 shows the exemplary simulated side that can be realized by the illustrative analogsimulation system being disclosed further below
Method.This method using original bottom terrain construction geological model space in block 702 to be started.Bottom configuration can be by with originally
Method known to the technical staff of field identifies the stratal surface in 3-d seismic data set to determine, those skilled in the art will also distinguish
Know for identification or infer other methods of the geometry of stratal surface.Such other methods include but is not limited to two-dimension earthquake
The explanation of line, other long-range imaging techniques, correlation logging record and spatially compare observation of appearing.It can allow to correct paleoslope
Variation or the other deformations for explaining face.
In block 704, user setting and water level and flow into the relevant analog parameter of condition, entry position including estimation and
The flow rate and sedimentary loading of the associated function as the time.These parameters can be based on by seismic interpretation person according to this
The explanation Gu flow direction that method known to the technical staff of field determines.It can be used using multiple simulations refinement initial parameter value
Some trial and error.Such method can be used similarly in frame 706 to construct model space grid and put down for depth
Equal flow velocity, the depth-averaged deposit concentration of each grain size category, flowing height, the center of gravity of silt carrying flow scapus provide initial
Value.Using the template of programming, these initial values also provide the initial perpendicular point of flow velocity and deposit concentration at each point map
Cloth section.
Then the system is by the loop iteration of frame 708-722 until reaching stop condition.Under normal conditions, stop condition
It is consistent with time step long number needed for the desired Geologic Time span of simulation, but other conditions are also suitable, including are reached
Target deposition depth, the unmatched threshold value more than relative target geologic structure, or computer graphical user circle is passed through by user
The vision-based detection in face.
In frame 708, which is applied to various current parameter values (depth-averaged velocity field, Mei Getu for flow equation
Depth-averaged deposit concentration, center of gravity, flowing height, bottom configuration and the inflow of each grain size category at point and other sides
Boundary's condition) come the depth-averaged flow velocity joined with new time correlation, depth-averaged deposition that simulated time step-length is advanced and obtained
Object concentration, center of gravity and flowing height.
In block 710, system deposits the depth-averaged of depth-averaged flow velocity, various grain size categories at each point map
Object concentration, center of gravity and flowing height determined as parameter value associated flowing template and deposit concentration template (one or
It is multiple).Such as depth-averaged Turbulent Kinetic and the other parameters of depth-averaged turbulent dissipation can be used for determining template.In frame
In 712, these templates are applied to depth-averaged flow velocity and depth-averaged deposit concentration, to obtain the vertical of each point map
It is distributed flow profile and vertical distribution deposit concentration section.
These sections are added together, and represent 3D velocity field and 3D deposit concentration field.These are used to count in frame 714
The deposit of each grain size category and the flux of fluid are calculated, including as bed surface shear stress, Turbulent Kinetic dissipate and spread, various
The erosion rate of grain size category, various grain size categories deposition rate, from corrode and deposition obtains to the change of bottom configuration,
Due to carrying and rolling out the influence of the various phenomenons of the change of convection current dynamic height secretly.By proposing these phenomenons in three-dimensional domain, in advance
Phase simulator will preferably explain the shearing dependence shadow of the varigrained speed dependence rate of settling, DIFFUSION IN TURBULENCE
Sound, concentration-dependant effect and particle interaction and those parameters with the combination dependence for such as corroding and depositing.
In block 716, (each granularity) of each point map net deposits are calculated and are recorded.The calculating
3D flowing and the concentration field that can be based not only at given point map, also based on these space and/or time-derivative.In mould
The combination of some parameters of tracking, the subsequent property for enabling to carry out any obtained geologic body are true in each unit of type
It is fixed.Tracking parameter can be the net quality or volume in every kind of granularity of each time step strong point deposition, allow for ground
Plastid deposition rate and age it is later determined that.
In frame 718, the divergence of fluid and sediment flux is calculated and for updating deposit concentration and fluid velocity profile.
Bottom configuration of the point map at given time step-length, including bottom ramp can be explained further in such update.
In frame 720, which quadratures to obtain depth to the deposit concentration section of the update of each grain size category
The center of gravity of average deposition object concentration and update.Similarly, it quadratures to fluid velocity profile to obtain the depth at each point map and put down
Equal velocity component.
In frame 722, simulator determines whether to have reached stop condition, and if it is, this method stops.
Fig. 8 shows an illustrative simulation system of the method for realizing Fig. 7.It includes via local area network (LAN)
104 are coupled to the personal workstation 102 of one or more multiprocessor computers 106, one or more of multiprocessor meters
Calculation machine 106 is coupled to one or more shared memory cells 110 via storage area network (SAN) 108 again.Personal workstation 102
It with the user interface for accomplishing simulation system, allows users to load data into system, to configure the behaviour with monitoring system
Make, and from system retrieval result (usually in the form of image data).Personal workstation 102 can take the shape of desktop computer
Formula, the desktop computer have graphically illustrate input and result data expression graphic alphanumeric display, and have so that
User can move file and execute the keyboard of the software of processing.LAN 104 provide multiprocessor computer 106 between and with
The high-speed communication of personal workstation 102.LAN 104 can take the form of ethernet network.
Multiprocessor computer 106 (one or more) provides parallel processing capability, enables at suitably promotion
Input data is managed to export result data.Each computer 106 includes multiple processors 112, distributed memory 114, inside
Bus 116, SAN interface 118 and LAN interface 120.The task of 112 pairs of each processor distribution operates, to solve entirely to ask
A part of topic, and facilitate at least part of whole result.Associated with each processor 112 is that storage application is soft
The distributed storage module 114 of part and the work data set used for processor.Internal bus 116 is via corresponding interface
118,120 inter-processor communication and the communication to SAN or lan network are provided.It is logical between the processor of different computers 106
Letter can be provided by LAN 104.
SAN 108 provides the high speed access to shared storage device 110.SAN 108 can take such as optical-fibre channel or
The form of infinite bandwidth technical network.Shared memory cell 110 can be using magnetic disk media for non-volatile data storage
Big, independent information memory cell.In order to improve data access speed and reliability, shared memory cell 110 can be by
It is configured to redundant array (" RAID ").
Processor 112 cooperative executes simulator software 901 shown in Fig. 9.Software 901 access shared storage device it
One to retrieve template library 902 and initial simulation parameters 904 (including bottom configuration, inflow and boundary condition).Then software 901 is
Two-dimensional depth mean model space generates initially and subsequent parameter value 906, including depth-averaged velocity component, for grain size category
Depth-averaged deposit concentration, center of gravity and the flowing height of range.In each time step strong point, vertical distribution flow velocity and deposit
Concentration profile 908 is being converted go back to extensive enzymatic hydrolysis space to be determined before moving forward to future time step-length, with
In the relevant influence of the various depositions of simulation.Software 901 is that each unit generates deposition in the unit as the function of time 910
The record of deposit.
Although cartesian coordinate has been used in above-mentioned explanation, other coordinate systems are also suitable, and can
To use.Once disclosed above be fully understood, many other change and modification those skilled in the art will be become it is aobvious and
It is clear to.It is intended to following claims to be interpreted comprising all such changes and modifications.
Claims (15)
1. a kind of for simulating the computer based method of the differentiation of sedimentary basin, comprising:
(a) at each point map, flowing template and at least one deposit concentration template are determined based on following:
For the one or more depth-averaged deposit concentrations and depth-averaged flow velocity of associated grain size category,
Each of the depth-averaged flow velocity and one or more of depth-averaged deposit concentrations are walked for given time
The point map of strong point；
(b) at each point map, by the flowing template be applied to the depth-averaged flow velocity and by it is described at least one sink
Product object concentration template is applied to one or more of depth-averaged deposit concentrations to obtain and be directed to the vertical of the point map
It is distributed fluid velocity profile and one or more vertical distribution deposit concentration sections, to rebuild needle at the given time step-length
One or more 3D deposit concentrations field and 3D velocity field to associated grain size category；
(c) at each point map, needle is calculated using the 3D velocity field and one or more of 3D deposit concentrations field
To the one or more sediment fluxes and fluid flux of associated grain size category；
(d) at each point map, divergence based on the fluid flux at the point map at given time step-length and
One or more divergences of one or more of sediment fluxes update the fluid velocity profile and one or more of depositions
Object concentration profile；
(e) at each point map, by the fluid velocity profile at the point map at given time step-length and described
One or more deposit concentration sections quadrature to calculate the depth-averaged flow velocity and one or more of depth-averageds
Deposit concentration, to obtain the 2D velocity field of update and one or more 2D deposit concentrations field of update；
(f) center of gravity of each point map is exported from one or more of deposit concentration sections；And
(g) based on the 2D velocity field of update, one or more 2D deposit concentrations field of update, center of gravity and flowing height come to one
Group two-dimensional flow equation solution, to calculate the depth-averaged flow velocity of future time step-length at each point map.
2. the method as described in claim 1 further includes using future time step-length as the given time step-length and repeating institute
It states determination, application, use, update, calculating, export and solves operation.
3. the method as described in claim 1, wherein at least one described deposit concentration template is determined for the point map
And it is applied to multiple granularity particular deposition objects of the respective depth average deposition object concentration of different grain size grade at the point map
One of concentration template.
4. the method as described in claim 1, wherein calculating one or more sediment flux considers fluid velocity profile, bed surface
Shear stress, erosion, deposits, clear water are carried secretly/are rolled out, Turbulent Kinetic dissipates and diffusion.
5. the method as described in claim 1:
At each point map, the deposit of at least one grain size category based on the point map at given time step-length is dense
Section and fluid velocity profile are spent to estimate erosion or deposition rate；And
At each point map, it is based at least partially on the erosion or deposition of the estimation of the point map at given time step-length
Rate updates flowing height.
6. method as claimed in claim 5, wherein stream of the template also based on the point map at given time step-length
Dynamic height determines.
7. the method as described in claim 1, wherein the determination is also based on the depth-averaged Turbulent Kinetic at the point map
With depth-averaged turbulent dissipation.
8. the method as described in claim 1, wherein sea of the update also based on the point map at given time step-length
Bottom landform, including base slope.
9. the method as described in claim 1, further includes:
At each point map, the fluid velocity profile based on the point map at given time step-length and one or more
A deposit concentration section estimates net deposits；And
Function as the time is each point map and depth, record at least one of such as the following group property: one or more grains
Spend volume of sediment, the granularity of deposition in each of net deposition rate in each of frequency range, one or more granularity frequency ranges
Distribution, sediment type and bed plane.
10. method as claimed in claim 9, wherein the estimation is also based on:
The fluid velocity profile of adjacent point map and one or more of deposit concentration sections；Or
The fluid velocity profile of the point map at given time step-length and one or more of deposit concentration sections
Time rate of change or
The fluid velocity profile of the point map at given time step-length and one or more of deposit concentration sections
Time and spatial variations rate.
11. the method as described in claim 1, wherein described count one group of two-dimensional flow equation solution also at each point map
Calculate one or more depth-averaged deposit concentrations at future time step-length.
12. the method as described in claim 1, wherein each flowing and concentration template can be expressed as
With constraint
Wherein U (x, y) and V (x, y) indicates that the component of the depth-averaged flow velocity of the function as position, Ci (x, y) indicate i-th
The depth-averaged deposit concentration and h (x, y) of the function as position of granularity frequency range indicate the stream of the function as position
Dynamic height.
13. the method as described in claim 1 is included at each point map, is at least partially based at given time step-length
The fluid velocity profile and one or more of deposit concentration sections at the point map record the function as depth
Net deposits.
14. a kind of Sedimentary Basin Evolution simulation system, the system comprises:
Memory with simulator software；And
It is coupled to the memory to execute the one or more processors of the simulator software, the software makes one
Or multiple processors execute method described in any one of preceding claims.
15. a kind of simulator software, which makes one or more when executing on the one or more processors
A processor is executed such as the claimed method for simulating the differentiation of sedimentary basin of any one of claims 1 to 13.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US14/478,805 US10108760B2 (en) | 2014-09-05 | 2014-09-05 | Sediment transport simulation with parameterized templates for depth profiling |
| US14/478,805 | 2014-09-05 | ||
| PCT/US2015/018250 WO2016036411A1 (en) | 2014-09-05 | 2015-03-02 | Sediment transport simulation with parameterized templates for depth profiling |
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| US (2) | US10108760B2 (en) |
| EP (1) | EP3189357B1 (en) |
| CN (1) | CN106605158B (en) |
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| US10108760B2 (en) * | 2014-09-05 | 2018-10-23 | Chevron U.S.A. Inc. | Sediment transport simulation with parameterized templates for depth profiling |
| US11199640B2 (en) * | 2017-07-27 | 2021-12-14 | Saudi Arabian Oil Company | Determining sediment source locations |
| CN107942381B (en) * | 2017-11-01 | 2020-01-10 | 中国矿业大学 | Quantitative prediction method for tight oil reservoir bedding joints |
| CN109141810B (en) * | 2018-07-25 | 2019-05-10 | 西安石油大学 | A kind of ancient turbidity current kinetic parameter restoration methods based on water channel configuration |
| CN109033725B (en) * | 2018-09-14 | 2020-05-05 | 中国水利水电科学研究院 | Estimation method for large-area bed surface shear stress of fixed bed river model test |
| CN111291459B (en) * | 2018-11-21 | 2022-02-08 | 中国农业大学 | Method and system for determining silt flux of pump station approach channel and forebay |
| WO2020109958A1 (en) | 2018-11-30 | 2020-06-04 | Chevron Usa Inc. | System and method for analysis of subsurface data |
| US11714208B2 (en) * | 2020-04-23 | 2023-08-01 | Saudi Arabian Oil Company | Methods and systems for gridding of salt structures |
| US11668855B2 (en) * | 2020-06-11 | 2023-06-06 | Saudi Arabian Oil Company | Method and system for sedimentary pathway prediction using geological and seismic data |
| CN114060016A (en) * | 2020-08-03 | 2022-02-18 | 中国石油天然气股份有限公司 | Estuary reservoir simulation device, estuary reservoir water drive simulation device and estuary reservoir water drive simulation method |
| CN112613750B (en) * | 2020-12-25 | 2022-08-09 | 中建三局绿色产业投资有限公司 | Sedimentation risk assessment method for deep sewage conveying tunnel |
| CN114781237B (en) * | 2022-04-08 | 2024-04-05 | 中国科学院南京地理与湖泊研究所 | Lake viscous sediment transport model modeling method based on high turbidity event investigation |
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| CN101903805A (en) * | 2007-12-21 | 2010-12-01 | 埃克森美孚上游研究公司 | Modeling in sedimentary basins |
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| WO2004099816A2 (en) * | 2003-04-30 | 2004-11-18 | Exxonmobil Upstream Research Company | Method for predicting properties of a sedimentary deposit from a thickness contour of the deposit |
| ITMO20040165A1 (en) * | 2004-06-30 | 2004-09-30 | Apparecchiature Idrauliche S P | PERFECTED FLUID MACHINE WITH RADIAL CYLINDERS. |
| EP1766439A2 (en) | 2004-07-01 | 2007-03-28 | ExxonMobil Upstream Research Company | Hydrodynamics-based gridding geologic modeling (hydro-gridding) |
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| WO2006036389A2 (en) | 2004-09-10 | 2006-04-06 | Exxonmobil Upstream Research Company | Numerical modeling evaluation of basin sedimentation properities |
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| US10108760B2 (en) * | 2014-09-05 | 2018-10-23 | Chevron U.S.A. Inc. | Sediment transport simulation with parameterized templates for depth profiling |
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2014
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| CN101903805A (en) * | 2007-12-21 | 2010-12-01 | 埃克森美孚上游研究公司 | Modeling in sedimentary basins |
| CN102834739A (en) * | 2010-12-17 | 2012-12-19 | 雪佛龙美国公司 | System and method for estimating geological architecture of a geologic volume |
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| AU2015312396A1 (en) | 2017-02-16 |
| EP3189357B1 (en) | 2021-09-08 |
| WO2016036411A1 (en) | 2016-03-10 |
| EP3189357A1 (en) | 2017-07-12 |
| CA2956177A1 (en) | 2016-03-10 |
| CN106605158A (en) | 2017-04-26 |
| AU2015312396B2 (en) | 2019-08-29 |
| US10671775B2 (en) | 2020-06-02 |
| US20160070829A1 (en) | 2016-03-10 |
| US10108760B2 (en) | 2018-10-23 |
| US20190026413A1 (en) | 2019-01-24 |
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